Duración de la licencia.

After assessing that the experimental manipulation worked on subject, we analyzed the measurement properties and the structural paths in our models. Partial Least Squares (PLS) was used to perform the analyses. First, we assess the measurement properties of our instrument. Then, we test the hypotheses regarding the choice of user strategies of adaptation, and the influence of espoused UA and IC.

4.6.1. Measurement Validation

The first step for the assessment of measurement properties was to test reliability. Since the constructs of our model are reflective, Cronbach’s alphas are appropriate for testing reliability (Gefen et al. 2000). Because IC1 and IC2 significantly decreased the overall construct reliability of Espoused IC construct, we dropped these items. This did not affect the content of the constructs because reflective items are interchangeable (Jarvis et al. 2003). As shown in Table 3-6 below, Cronbach’s alphas range from .73 to .84, which is within the range of commonly accepted values.

Second, we tested convergent and discriminant validity (Boudreau et al. 2001). For that purpose, we performed a Principal Component Analysis (PCA) with each pair of coping strategies of adaptation constructs plus espoused cultural values. The PCA led us to delete UA4 due to poor psychometric properties. Any item that loaded at a level above .40 (values in bold in Table 3-6) on an unintended construct was a candidate for deletion because it is a threat to discriminant validity (Gefen et al. 2000). At this point, all items loaded cleanly on

explained and the Kaiser Meyer Olkin (KMO) measure of sampling adequacy. The results of the PCAs are shown in Table 4-6 below.

Table 4.6. Principal Component Analyses1

BM and BS Strategies DH and SP Strategies

Item BM BS EUA EIC Item DH SP EUA EIC

BM2 .85 -.13 .09 .06 DH2 .85 -.27 -.04 -.04 BM3 .83 -.14 .05 .06 DH3 .84 -.32 .03 .01 BM1 .79 -.01 .18 .04 DH1 .84 -.19 .01 -.01 BM4 .70 -.16 .12 .05 DH4 .73 -.31 .09 -.05 BM5 .63 -.26 .14 .01 SP4 -.39 .83 -.08 .05 BS4 -.23 .77 -.09 -.07 SP3 -.34 .81 -.13 .02 BS5 -.29 .75 -.07 -.05 SP2 -.31 .78 .02 -.02 BS2 -.10 .72 -.13 .04 UA2 .03 -.10 .84 .12 BS1 -.01 .66 .18 .07 UA1 .08 .01 .83 .08 UA2 .05 -.07 .85 .12 UA3 -.04 -.06 .79 .06 UA1 .21 -.09 .79 .09 IN4 .06 .14 .16 .84 UA3 .21 .07 .76 .05 IN3 -.01 -.07 -.06 .80 IN4 .02 .00 .15 .85 IN5 -.11 -.01 .19 .73 IN3 .15 .06 -.09 .79 IN5 -.01 -.06 .19 .74 V.E. 28.38% 14.60% 10.51% 9.67% V.E. 34.50% 18.82% 11.80% 7.02%

KMO Measure of Sampling Adequacy = 0.78 KMO Measure of Sampling Adequacy = 0.79

Total V.E. = 63.16 % Total V.E.= 72.15 %

Cronbach's Alphas: BM=.844, BS=.728, DH=.886, SP=.849, EUA=.767, EIC=.713

1_{BS1, EIC1, EIC2 and EUA4 have been excluded from analyses following an iterative process in order to refine}

the instrument.

2_{V.E. = Variance Extracted}

Convergent validity can be assessed when the items are significantly related with their intended constructs. All of the items in the PCA load at least .63 on their intended construct, which shows appropriate convergent validity. Since items load more highly on their intended construct than on any other construct (Boudreau et al. 2001), discriminant validity was reasonable. Furthermore, since no item loadings exceeded .40 on constructs other than those on which they are intended to load, we can therefore conclude that the instrument has appropriate discriminant validity (Straub et al. 2004).

4.6.2. Scales for OpChoice and ThChoice

After the test of measurement properties, we had to build scales to measure user preference for one coping strategy of adaptation over another. We elaborated continuous scales

representing user preferred coping strategy over the other. Since subjects had the possibility of stating their perceptions for two strategies for each scenario, we needed a scale that would predict which one of the two strategies subjects would be more likely to choose. The scales were built by taking the means of items for each strategy constructs. Then we calculated the difference between one strategy and the other such as:

Mean (BMi ,…,BMn) – Mean (BSj,…,BSz) > 0 the user prefers the BM Strategy

Mean (BMi ,…,BMn) – Mean (BSj,…,BSz) < 0 the user prefers the BS Strategy Similarly,

Mean (DHi ,…,SPn) – Mean (DHj,…,SPz) > 0 the user prefers the DH Strategy

Mean (DHi ,…,SPn) – Mean (DHj,…,SPz) < 0 the user prefers the SP Strategy

Our basic assumption is that in a scenario in which there are many opportunities and when an individual has control, s/he will choose BM, and therefore BM>BS. When s/he does not have control, s/he will choose BS, and therefore BS>BM. As stated earlier, OpChoice (or OpC)is

the scale for strategy choice when the situation shows many opportunities, and ThChoice (or

ThC)is the scale of strategy choice when the situation is threatening.

4.6.3. Validity

Partial Least Squares (PLS) was used to further analyze the validity of the measurement. Tests were performed with SmartPLS (Ringle et al. 2005). PLS is particularly appropriate for our study since it has fewer distributional assumptions than covariance based applications such as LISREL or AMOS. Also, another major reason for choosing PLS is that, following Chin et al. (2003) and Goodhue et al. (2007), the PLS approach is more powerful than regression analysis with its summated scales for the detection of moderation effects. Because

appropriate for testing.

Convergent and discriminant validity can be assessed through the analyses of cross loadings. The cross loadings in Table 3-7 below indicate that all items load significantly on their intended constructs. The instrument thus shows appropriate convergent validity. Also, the results in Table 4-7 provide evidence that items load greater on their intended constructs than on any other construct, which demonstrates discriminant validity (Boudreau et al. 2001).

Table 4.7. Cross Loadings

Item Cross Loadings - Opportunity Scenario Cross Loadings -Threat Scenario

EIC EUA EIC EUA

EIC3 .77 .08 .44 .08 EIC4 .87 .23 .82 .23 EIC5 .76 .22 .91 .22 EUA1 .18 .88 .21 .85 EUA2 .21 .84 .24 .90 EUA3 .16 .75 .19 .69

OpC = OpChoice, strategy choice when the situation has many opportunities ThC = ThChoice, strategy choice when the situation has many threats EIC = Espoused Individualism-Collectivism

EUA = Espoused Uncertainty Avoidance

A second criteria to assess discriminant validity is the analysis of the Average Variance Extracted Matrix (AVE). The values on the diagonal have to be greater than values outside the diagonal. While the literature according to Boudreau et al. (2001) does not tell us how much greater the values on the diagonal should be, we are confident that those in Table 4-8 below prove discriminant validity, confirming prior results.

Table 4.8. AVE Matrix

Items AVE - Opportunity Scenario AVE -Threat Scenario

CR AVE EIC OpC EUA CR AVE EIC EUA ThC

EIC 0,84 0,64 0,80 0,78 0,56 0,75

EUA 0,86 0,68 0,22 0,82 0,86 0,67 0,26 0,82

Opc/ThC1 _{- - 0,11 0,00 1,00 - - -0,09 0,12 1,00}

1_{Opc = OpChoice, ThC = ThChoice; EIC= Espoused Individualism-Collectivism; EUA = Espoused Uncertainty} Avoidance

CR = Composite Reliability; AVE=Average Variance Extracted

SmartPLS also provides reliability statistics through its Composite Reliability. Similar to Cronbach’s Alpha, this statistics is at acceptable levels, ranging from .78 to .86 for espoused

cultural values.

Overall, given the results above, we can conclude that our instrument has acceptable measurement properties.